English abstract

This investigation intends to classify the students of the University of Informatics Sciences according to their academic behaviour using a set of Data Mining techniques like clustering, decision trees and inductive learning algorithms. The main goal of this work is to find hidden patterns and rules that define this behaviour, based on the relationship established between the scholarship level of the student’s parents, and their academic origins with their grades in the first year of their career. These results can help to improve the quality of the academic process in the UCI.